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Modularity of Sequence Learning Systems in Humans

  • Steven W. Keele
  • Tim Curran

Abstract

Humans excel at a variety of learned and highly skilled activities in which complex sequential behavior is distributed over time. The major theme of this chapter concerns the hypothesis that sequence learning and production of sequences of activities involves not a single function, but rather is made up of multiple components. For example, in playing a piano, pitch is mapped to key position and key position is mapped to the motor system for bringing the arms, hands, and fingers to the keys. In addition to this spatial mapping, the pianist must learn the sequence of notes or keys that correspond to a piece of music. The sequential representation must indicate not only which note or key is next in a series, but must also specify the intervals at which the keys should be hit and with what intensity. In other activities, dancing for example, trajectory through space, and not just the target of movement, must be specified. It is likely that some of these functions are independent of one another, both in the psychological sense that one function can be affected with minimal or no influence on another, and in a neurobiological sense in that they depend on different brain regions. This chapter will focus on a selected aspect of skill, the representation of learned sequences, and will consider only those representations that specify the succession of events. One of the issues to be addressed is the relationship between the representation of a sequence and the motor system that actually produces the sequence. Evidence will be presented that sequence representation is relatively abstract and independent of the implementation system. A second line of evidence to be presented suggests that the sequential representation itself has constituent parts or modules.

Keywords

Secondary Task State Unit Sequence Learning Hide Unit Implicit Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • Steven W. Keele
    • 1
  • Tim Curran
    • 1
  1. 1.Department of Psychology, College of Arts and SciencesUniversity of OregonEugeneUSA

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